IDEAS home Printed from https://ideas.repec.org/p/cqe/wpaper/1110.html
   My bibliography  Save this paper

Demand Matters: German Wheat Market Integration 1806-1855 in a European Context

Author

Listed:
  • Martin Uebele

Abstract

This study analyzes annual wheat prices in 13 German cities in the years 1806 to 1855, together with wheat price series from 44 other European and American cities. The method used is a dynamic factor model, which allows for distinguishing common price uctuations on international and national levels. I find a significant increase of price synchronization between German cities and international markets, between the first and the second quarter of the 19th Century. This is probably mainly due to the increased demand for food imports in Britain and the disappearance of political barriers, as well as economies of scale and gradual improvements to existing transportation technology. Within Germany, I find increasing common price uctuations in Mannheim and Munich, which arguably refl ects a customs union effect. Tree ring records as indicators of general plant growth conditions indicate that comovement was not driven by exogenous shocks.

Suggested Citation

  • Martin Uebele, 2010. "Demand Matters: German Wheat Market Integration 1806-1855 in a European Context," CQE Working Papers 1110, Center for Quantitative Economics (CQE), University of Muenster.
  • Handle: RePEc:cqe:wpaper:1110
    as

    Download full text from publisher

    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/CQE_WP_11_2010.pdf
    File Function: Version of February, 2010
    Download Restriction: no

    References listed on IDEAS

    as
    1. Lux, Thomas, 2008. "The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
    2. Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2011. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(2), pages 314-343, Spring.
    3. Calvet, Laurent & Fisher, Adlai, 2001. "Forecasting multifractal volatility," Journal of Econometrics, Elsevier, pages 27-58.
    4. Laurent E. Calvet, 2004. "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 49-83.
    5. Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 53-89.
    6. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    7. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    8. Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2011. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Journal of Financial Econometrics, Society for Financial Econometrics, pages 314-343.
    9. Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2011. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Journal of Financial Econometrics, Society for Financial Econometrics, pages 314-343.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, pages 307-327.
    11. Umberto Cherubini & Elisa Luciano, 2001. "Value-at-risk Trade-off and Capital Allocation with Copulas," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 235-256, July.
    12. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    13. Clive W.J. Granger, 1999. "Outline of forecast theory using generalized cost functions," Spanish Economic Review, Springer;Spanish Economic Association, vol. 1(2), pages 161-173.
    14. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
    15. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    16. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    17. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    18. Huang, Jen-Jsung & Lee, Kuo-Jung & Liang, Hueimei & Lin, Wei-Fu, 2009. "Estimating value at risk of portfolio by conditional copula-GARCH method," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 315-324, December.
    19. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kopsidis, Michael & Wolf, Nikolaus, 2012. "Agricultural Productivity Across Prussia During the Industrial Revolution: A Thünen Perspective," The Journal of Economic History, Cambridge University Press, vol. 72(03), pages 634-670, September.
    2. Uebele, Martin, 2011. "National and international market integration in the 19th century: Evidence from comovement," Explorations in Economic History, Elsevier, vol. 48(2), pages 226-242, April.
    3. Martin Uebele & Daniel Gallardo-Albarrán, 2015. "Paving the way to modernity: Prussian roads and grain market integration in Westphalia, 1821-1855," Scandinavian Economic History Review, Taylor & Francis Journals, pages 69-92.
    4. Keller, Wolfgang & Shiue, Carol Hua, 2013. "The Trade Impact of the Zollverein," CEPR Discussion Papers 9387, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    market integration; 19th Century; dynamic factor analysis; wheat prices; Germany;

    JEL classification:

    • N70 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - General, International, or Comparative
    • N71 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - U.S.; Canada: Pre-1913
    • N73 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - Europe: Pre-1913
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F15 - International Economics - - Trade - - - Economic Integration
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cqe:wpaper:1110. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Susanne Deckwitz). General contact details of provider: http://edirc.repec.org/data/cqmuede.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.